| Automatic identification and counting of small size pests in greenhouse conditions with low computational cost | |
Xia, CL ; Chon, TS; Ren, ZM; Lee, JM; Lee, JM (reprint author), Pusan Natl Univ, Sch Elect Engn, Pusan 609735, South Korea. jmlee@pusan.ac.kr
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| 发表期刊 | ECOLOGICAL INFORMATICS
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| ISSN | 1574-9541 |
| 2015-09-01 | |
| 卷号 | 29页码:139-146 |
| 关键词 | Pest Monitoring Computational Complexity Mahalanobis Distance Greenhouse Management |
| DOI | 10.1016/j.ecoinf.2014.09.006 |
| 产权排序 | [Xia, Chunlei] Chinese Acad Sci, Yantai Inst Coastal Zone Res, Res Ctr Coastal Environm Engn & Technol Shandong, Yantai 264003, Peoples R China; [Xia, Chunlei; Lee, Jang-Myung] Pusan Natl Univ, Sch Elect Engn, Pusan 609735, South Korea; [Chon, Tae-Soo] Pusan Natl Univ, Dept Biol Sci, Pusan 609735, South Korea; [Ren, Zongming] Shandong Normal Univ, Coll Life Sci, Jinan 250014, Peoples R China |
| 作者部门 | 山东省海岸带环境工程技术研究中心 |
| 英文摘要 | We propose an automatic pest identification method suitable for large scale, long term monitoring for mobile or embedded devices in situ with less computational cost. A procedure of segmentation and image separation was devised to identify common greenhouse pests, whiteflies, aphid and thrips. Initially, the watershed algorithm was used to segment insects from the background (i.e., sticky trap) images. Color feature of the insects were subsequently extracted by Mahalanobis distance for identification of pest species. Accuracy and computational costs were evaluated across different image resolutions. The correlation of determination (R-2) between the proposed identification scheme and manual identification were high, showing 0.934 for whitefly, 0.925 for thrips, and 0.945 for aphids even with low resolution images. Comparing with the conventional methods, pests were efficiently identified with low computational cost. Optimal image resolution for species identification regarding long-term survey was discussed in practical aspect with less computational complexity. (C) 2014 Elsevier B.V. All rights reserved. |
| 文章类型 | Article |
| 收录类别 | SCI |
| 语种 | 英语 |
| 关键词[WOS] | MAHALANOBIS DISTANCE ; STICKY TRAPS ; IMAGE ; MANAGEMENT ; ALGORITHM ; SYSTEM ; TIME |
| 研究领域[WOS] | Environmental Sciences & Ecology |
| WOS记录号 | WOS:000361776400006 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.yic.ac.cn/handle/133337/10020 |
| 专题 | 中国科学院海岸带环境过程与生态修复重点实验室_海岸带环境工程技术研究与发展中心 中国科学院海岸带环境过程与生态修复重点实验室 |
| 通讯作者 | Lee, JM (reprint author), Pusan Natl Univ, Sch Elect Engn, Pusan 609735, South Korea. jmlee@pusan.ac.kr |
| 推荐引用方式 GB/T 7714 | Xia, CL,Chon, TS,Ren, ZM,et al. Automatic identification and counting of small size pests in greenhouse conditions with low computational cost[J]. ECOLOGICAL INFORMATICS,2015,29:139-146. |
| APA | Xia, CL,Chon, TS,Ren, ZM,Lee, JM,&Lee, JM .(2015).Automatic identification and counting of small size pests in greenhouse conditions with low computational cost.ECOLOGICAL INFORMATICS,29,139-146. |
| MLA | Xia, CL,et al."Automatic identification and counting of small size pests in greenhouse conditions with low computational cost".ECOLOGICAL INFORMATICS 29(2015):139-146. |
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| Automatic identifica（1225KB） | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 | |
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